Past exam of the calculus of variations course of the University of Oxford / 2011 / 2 / a

The variational terminology refers to the size of a neighborhood, rather than weak versus strong convergence in a Banach space. The definitions in the two numbered children giveThe second implication holds because smallness in $W^{1,\infty }$ implies smallness in the uniform norm. Reverse implications need not hold.

For differentiable $f$ in its slope variable, define the Weierstrass excess functionThe strengthened Weierstrass condition means that some $\delta >0$ givesIt requires support at nearby heights and nearby reference slopes, while the trial slope $q$ is arbitrary. Requiring this only exactly on the curve is the unstrengthened necessary condition.

A standard Weierstrass sufficient condition assumes the usual $C^2$ smoothness of $f$, $u\in \mathcal{A}\cap C^1$, the weak Euler-Lagrange equation, a coercively positive second variation, and the strengthened condition above. Explicitly, for some $c>0$,for zero-endpoint variations. Then $u$ is a strong local minimizer. If the excess is strictly positive for $q\ne p$ throughout the tube, the strong minimum is strict. The second-variation hypothesis supplies a neighboring field of extremals. Its slope $p(x,y)$ gives the comparison identityfor uniformly close admissible $v$. This explains how the condition controls competitors with large derivatives.

A weak local minimizer of a variational integral is an admissible $\bar{u}$ for which there is $\epsilon >0$ such thatBoth the function and its first derivative must remain uniformly close, up to the almost-everywhere convention for the derivative.

A strong local minimizer of a variational integral is an admissible $\bar{u}$ for which there is $\epsilon >0$ such thatThe competitor's derivative need not be close. This compares with a larger family of competitors, which is why it is the stronger minimality property.